SR AI Engineer (Techno-functional)/PERM/Logistics

Argyll Scott; Hong Kong; On-site; HKD 900,000 - 1,500,000; Full time

Job summary

Argyll Scott is seeking a Senior technofunctional AI Engineer for a C-level engagement within a leading global supply chain and logistics group. The role centers on building autonomous AI systems, agentic workflows, and decision-support tools that accelerate executive decision-making.

You will translate business objectives into production software and collaborate with central IT to ensure governance, security, and scalable support, delivering low-latency dashboards for the C-suite.

Qualifications

• 6+ years of hands-on software, data, or AI engineering experience.
• Proven experience deploying LLMs in production.
• Advanced Python skills for backend development, automation, and data pipelines.
• Hands-on cloud engineering experience (AWS, Azure, or GCP) with CI/CD and MLOps practices.
• Design clean visual interfaces and dashboards for executive use.
• Experience building scalable, secure systems handling sensitive data.
• Bachelor's degree in Computer Science, Software Engineering, Data Science, Mathematics, or related field.

Responsibilities

• Design and deploy autonomous agentic workflows and RAG data pipelines.
• Build scalable backend services, APIs, and data workflows with CI/CD and cloud infra.
• Establish LLM lifecycle approaches (packaging, versioning, deployment, monitoring).
• Handoff production solutions to central tech while maintaining governance and security.
• Develop low-latency reporting tools and executive dashboards for C-suite decisions.

Skills

LLMOps

RAG architectures

Advanced Python

Cloud engineering

REST APIs

Education

Bachelor's degree in Computer Science or related field

Tools

Docker

Kubernetes

MLflow

Kubeflow

Job description

Location: Hong Kong

Industry: Supply Chain & Logistics

Employment Type: Full-time, Permanent

Position Title: Sr. AI Engineer (TechnoFunctional) - C-level engagement

Position Summary

On behalf of our client, a leading global supply chain and logistics group, we are seeking an Senior technofunctional AI Engineer. The organization is expanding artificial intelligence as a core operational capability-treating intelligent tools as mission-critical, secure, and scalable enterprise software.

This is a highly autonomous, hands-on builder role with high C-level visibility, focusing on engineering practical AI systems, agentic workflows, and decision-support tools that directly accelerate strategic executive decision-making. Serving as a key technical partner to C-suite leadership, you will translate high-level commercial objectives into production-ready software while collaborating with central IT teams to ensure enterprise governance, security guardrails, and long-term supportability.

Key Responsibilities

• Agentic Workflows & Data Ingestion: Design and deploy autonomous agents, Retrieval-Augmented Generation (RAG) architectures, and automated pipelines to ingest, structure, and synthesize complex operational data from enterprise databases and third-party logistics feeds.
• Production Software Engineering: Build and maintain scalable backend services, APIs, and data workflows using modern software engineering disciplines (CI/CD, version control, automated testing, cloud infrastructure). Apply practical analytics and light machine learning where applicable to improve decision quality.
• LLMOps & Lifecycle Management: Establish end-to-end pipelines for packaging, versioning, deploying, monitoring, and rolling back LLMs and agentic workflows. Rapidly prototype bespoke software tools and systematically mature successful prototypes into production-grade services.
• Enterprise Governance & Handoff: Transition productionized solutions to central technology teams for long-term operational ownership (e.g., enterprise ERP integrations) while retaining oversight of bespoke executive tools. Ensure strict adherence to security-by-design, access controls, and data privacy guardrails.
• Executive Decision Systems: Develop low-latency reporting tools, clean visual interfaces, and executive dashboards that aggregate multi-source data to inform C-suite strategic planning and operational decision-making.

Candidate Requirements

Essential Qualifications & Experience

• 6+ years of hands-on software, data, or AI engineering experience with a demonstrated track record of shipping production-ready applications.
• Proven experience deploying LLMs in production, including hands-on work with agent frameworks, RAG architectures, vector databases, and tool orchestration.
• Advanced Python skills for backend development, automation, and data pipelines, alongside experience building REST/gRPC APIs and microservices.
• Hands-on cloud engineering experience (AWS, Azure, or GCP) paired with a solid grounding in CI/CD, testing, infrastructure automation, and core MLOps/LLMOps practices.
• Demonstrated ability to design clean visual interfaces and dashboards tailored for executive-level decision-makers.
• Experience engineering scalable, secure systems designed to handle sensitive commercial or operational data.
• Bachelor's degree in Computer Science, Software Engineering, Data Science, Mathematics, or a related technical discipline.

Desirable Qualifications

• Familiarity with containerization and orchestration (Docker, Kubernetes) and MLOps frameworks (e.g., MLflow, Kubeflow).
• Background developing technical tools in high-consequence operational or financial decision environments (e.g., supply chain, logistics, quantitative research, trading, or asset management).
• Exposure to enterprise ERP architectures and specialist third-party supply chain or market data feeds.